In general, touch screen technology has advanced in recent years. The ability to directly touch and manipulate data on the screen without using any intermediary devices has a very strong appeal to users. In particular, novices tend to benefit most from the directness of touch screen displays. A fast learning curve and inherent robustness (no movable parts) make touch screens an ideal interface for interacting with public installations, such as information kiosks, automated teller machines, ticketing machines, retail cashier systems for employee or customer use, voting machines, or gambling devices.
While touch screen use has become widespread in such special purpose applications, its presence in more general computing devices such as personal computers and laptops, for example, is far less prevalent. The slow adoption of touch screens into more general computing devices may be attributed to known issues of relatively high error rates and arm fatigue. In addition, the variable size of human fingers and the lack of sensing precision can make touch screen interactions difficult at best.
Due to technical restrictions, most commercially available touch screen devices currently in use are only capable of tracking a single point on the surface of the device. However, multi-touch devices are slowly emerging into the marketplace. Unfortunately, the multi-touch screens introduce further challenges in addition to those currently existing in single-touch screens. For instance, the underlying technology of multi-touch sensitive devices often makes their input noisier, thus requiring further considerations for filtering the undesirable noise and/or distinguishing the correct input from the noise.
These issues become especially problematic when running program applications developed for a traditional mouse interface on a multi-user touch screen. This is primarily because current WIMP (windows, icons, menus, and pointing) user interfaces require frequent selection of very small targets (e.g., about 4 pixels or less). For example, window resize handles are often just 4 pixels wide. Noisy input, lower tracking resolution, and a large potential touch area of a finger tend to create significant selection problems.
Furthermore, fingertips can occlude small targets depriving users of visual feedback during target acquisition. The user's hands and arms may contribute to the occlusion problem. Depending on screen orientation, the user may be forced to either look “under hand” (with horizontally positioned screens) or “over hand” (with angled or vertically positioned screens). Finally, it is often difficult to decide the optimal point in the finger's contact area which should anchor the cursor, leaving the usual choice to the center of mass. This can lead to a small but pervasive disconnect between the user's expectations regarding cursor position and what is actually being sensed and computed. These issues have been recognized by researchers who have proposed several solutions: adding a fixed cursor offset, enlarging the target area, and providing on-screen widgets to aid in selection. However, these solutions tend to fall short either by introducing new problems or by only improving some problems and leaving others unresolved. For example, the fixed cursor offset provides a cursor with a fixed offset above the tip of a finger when the user is touching the screen. Lifting the finger off the screen triggers a selection (“click”). While this method is effective for most targets sizes, it has been found ineffective when the target size is smaller than 4 pixels. In addition, the risk or frequency of unintentional clicks may still be undesirably high.
Others have explored cursor stabilization improvements that effectively slow down the cursor movement in various regions around the initial finger contact point. While this method performed well for the target acquisition task, precise steering tasks, such as drawing, would be hard due to varying cursor speed. More recently, several on-screen widgets have been explored for increasing precision while selecting small targets on a touch screen. However, their interactions were designed to be used with touch screens capable of reporting only a single contact point and therefore the users were required to execute multiple discrete steps before selecting the target. These steps were delimited by the user lifting their finger from the screen, thus impeding the overall interaction performance. Losing overview or context is another main drawback of this technique which can cause significant problems in many applications.
Increasing the relative size of screen targets has also been explored by scaling the display space or scaling the motor space. This work experimented with hand gestures that activated various levels of fish-eye distortion in the interface to facilitate target selection. Techniques that adaptively increase the motor space while leaving the displayed image unchanged show promising results without introducing screen distortions, but require that the system know all target locations. This information might not be available in many of today's applications. More importantly, such techniques require the use of a relative pointing device such as a mouse. Without such devices, they introduce an unpredictable cursor offset when applied directly to an absolute pointing device such as a touch screen.
Research in the area or multi-touch screens has identified that most current user interfaces require an interaction model consisting of at least 3 different states: out-of-range, tracking, and dragging. However, many touch sensitive devices can only reliably sense location in one state thus making it hard to disambiguate between dragging and tracking (hover). The use of a stylus (pen) is generally preferred in many interfaces that require precise interactions. However, while a stylus has a much smaller tip, the associated issues with hand tremor and resolution make the selection task of small targets more difficult than with a mouse.